CN102171572A - Biomarkers and assays for diabetes - Google Patents

Biomarkers and assays for diabetes Download PDF

Info

Publication number
CN102171572A
CN102171572A CN2009801179321A CN200980117932A CN102171572A CN 102171572 A CN102171572 A CN 102171572A CN 2009801179321 A CN2009801179321 A CN 2009801179321A CN 200980117932 A CN200980117932 A CN 200980117932A CN 102171572 A CN102171572 A CN 102171572A
Authority
CN
China
Prior art keywords
t2dm
diabetes
biomarker
protein
disease
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN2009801179321A
Other languages
Chinese (zh)
Inventor
兰德尔·W·尼尔森
查德·R·博格斯
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Publication of CN102171572A publication Critical patent/CN102171572A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/46Assays involving biological materials from specific organisms or of a specific nature from animals; from humans from vertebrates
    • G01N2333/47Assays involving proteins of known structure or function as defined in the subgroups
    • G01N2333/4701Details
    • G01N2333/4713Plasma globulins, lactoglobulin
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/575Hormones
    • G01N2333/62Insulins
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/76Assays involving albumins other than in routine use for blocking surfaces or for anchoring haptens during immunisation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/435Assays involving biological materials from specific organisms or of a specific nature from animals; from humans
    • G01N2333/775Apolipopeptides
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/795Porphyrin- or corrin-ring-containing peptides
    • G01N2333/805Haemoglobins; Myoglobins
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/81Protease inhibitors
    • G01N2333/8107Endopeptidase (E.C. 3.4.21-99) inhibitors
    • G01N2333/8139Cysteine protease (E.C. 3.4.22) inhibitors, e.g. cystatin
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00Detection or diagnosis of diseases
    • G01N2800/04Endocrine or metabolic disorders
    • G01N2800/042Disorders of carbohydrate metabolism, e.g. diabetes, glucose metabolism

Abstract

The present invention is directed to novel biomarkers and combinations thereof. The present invention also provides assays and data evaluation methods related to the detection and monitoring of diseases, particularly, diabetes. In particular, the biomarkers in accordance with the present invention include, but are not limited to, modified forms of nominally wild-type proteins, such as Gc-Globulin or GcG (also known as Vitamin D binding protein), beta-2-microglobulin (b2m), cystatin C (cysC), Albumin and Hem A&B. Particular forms of diabetes contemplated by the methods of the present invention include, but are not limited to, type 1 diabetes (T1D), type 2 diabetes (T2DM), pre-T1D and pre-T2DM. The present invention also provides methods of detecting multiple biomarkers in a single assay and to employ data evaluation methods that is able to accurately use these data in the determination and monitoring of diseases, such as diabetes.

Description

The biomarker and the mensuration that are used for diabetes
Background of invention
Suffer from diabetes (totally suffering from 1 type and diabetes B) near 24,000,000 American according to estimates, about 1/3rd of these philtrums do not know itself to suffer from disease.Diabetes conservatively estimate to cause the 6th inducement of American's death, and find morbidity rate (having bigger number percent) out of proportion in the minority crowd.Increase from 10 years of nineteen ninety to 2000 year with about 50% ratio, estimate that diabetes can double popular in ensuing 40 years, and be considered to the global threat to the race to a certain extent, cause mortality ratio to increase, quality of life descends and the caring cost increases.In 2007, estimate that the total expenses of diabetes care is 1,740 hundred million $, wherein only on the medicine expenditure, just accounted for the great majority of total expenses.Annual diabetes cause 12,000-24,000 new blind case, and be the inducement of renal failure, about 150,000 patients that cause having end-stage renal disease only on dialysis treatment annual cost surpass 7,500,000,000 $.It also causes 60% atraumatic LEA (at 2002 82,000th, because diabetes cause), and the expense of curing the disease from pricing equals approximately annual cost 8,000,000,000 $ of national expense and carries out LEA.Consider these main defectives (dead or wounded or disabled), can prevent the influence of (or postponing at least) diabetes by early detection and treatment.The non-drug therapy regimen is paid close attention to life style is interfered with the form that changes the common food of being eaten, loses weight and carry out system's exercise.Sulphur urea or metformin are passed through in standard drug therapy to acute diabetes, and the insulin formula of shortterm effect form or long term form.Recently, demonstrate as novel drugs and can expect glucose level control by dipeptidyl peptidase-iv inhibitor (for example, Januvia and Galvus) representative.In addition, there is the medicine that surpasses 350 kinds to improve candidate scheme at present and develops (for example, GLP-1 variant, DPP-IV inhibitor and SGLT2 inhibitor), make diabetes become about second health threat that is only second to cancer to health research exploitation aspect.For importantly in early days diagnosis of the timely processing of all treatments, preferably the susceptibility by the biomarker that carries out in the biofluid that obtains easily detects.It is also important that (particularly consider some novel drugs research and development) utilize biomarker to come the validity of monitor therapy.
At present, in detecting, diabetes utilize two kinds of biomarkers usually: blood sugar and glycosylated hemoglobin (HbA1c).These two kinds of labels are to the direct monitoring (glucose) of blood sugar increasing in the blood flow and indirect monitoring (HbA1c) substantially.Each label is detecting and is monitoring the use that himself is arranged in the diabetes.Glucose is the direct measurement to blood sugar increasing, and is used for assisting to diagnosis of diabetes and treatment monitoring.HbA1c is the measurement of long term exposure in rising blood sugar, and markers is generally equal to the half life period (60-90 days) in the haemoglobin body, and is generally used for monitoring ongoing treating diabetes.Two kinds of labels all can utilize single clinical detection platform (for example, Beckman Coulter SYNCHRON) to measure, but each needs different mensuration schemes.Glucose utilizes enzymatic determination (hexokinase) to utilize spectrophotometric to read usually and measures, and HbA1c utilizes the direct spectrophotometry of total hemoglobin combined with the turbidity immunosupress that is suitable for measuring glycosylated hemoglobin and measures.In addition, many somes care devices (for example, Therasense Freestyle (this and gloomy profit is comfortable) (blood sugar) and Bio-Rad in2it (HbA1c)) can be used for two kinds of labels, demonstrate to translate the biomarker that more approaches the patient and the importance of mensuration.
Two kinds of analyses all depend on the accurate measurement that the relatively small amount in the target organism label is changed.In rapid blood sugar test, be considered to normally less than the blood sugar level of 100mg/dL, and greater than the blood sugar level of the 126mg/dL diabetes of being thought suffering from; On concentration, has about 25% variation.Similarly increase is relevant with oral glucose tolerance test (OGTT), and the blood sugar level less than 140mg/dL is considered to normally herein, and suffers from diabetes (about 40% variation) greater than the blood sugar level indication of 200mg/dL.Not to measure absolute concentration, but measure glycosylated hemoglobin with respect to total hemoglobin.HbA1c value less than 6% is the desired value for normal individual or the diabetic that receives treatment, and it is relatively poor greater than 7% value indication treatment, and the variation that can get permission to treat (just, little variation to 16% is considered to important on relative quantity).For mixed problem, in these values, there is the gray area (fasting blood-glucose of 100-125mg/dL just; OGTT=140-200mg/dL; And HbA1c=6-7%), above-mentioned " prediabetes " state that causes usually.
Therefore, health status and prediabetes state are distinguished or the prediabetes state is distinguished and need be measured more accurately than the available measurement of current obtainable single labelled thing with diabetic disease states.
Therefore, need the label and the mensuration of the multiple novelty of research and development, it can correctly detect diabetes and monitoring therapeuticing effect when utilizing the suitable data appraisal procedure.
Summary of the invention
The present invention discerns new biomarker and its composition.The present invention also provides about detecting and monitor the mensuration and the data assessment method of diabetes.Concrete, biomarker according to the present invention includes but not limited to, specified wild-type protein variant form.The protein variations of the present invention's expection can be undertaken by method well known in the art, includes but not limited to that genetic mutation (GM) is translated the back and modified (PTM) and/or metabolism change (MA).Particular form by the diabetes of the inventive method expection includes but not limited to type 1 diabetes (T1D), diabetes B (T2DM), type 1 diabetes early stage (pre-T1D), diabetes B early stage (pre-T2DM).Biomarker, mensuration and data assessment method also hint the other diseases that causes the protein relative variability.The most important thing is and clearly to detect GM under the situation of wild formal protein, the mensuration ability of PTM and MA protein form existing.The important in addition ability that is to detect multiple biomarker and application data appraisal procedure (can in diabetes are made a definite diagnosis and monitored, correctly use these data) with a kind of mensuration.
Therefore, an aspect of of the present present invention relates to new biomarker, includes but not limited to, Gc-globulin or GcG (also known) with protein in conjunction with vitamin D, B2M (b2m), cysteine proteinase inhibitor C (cysC), albumin (Albumin) and HemA﹠amp; B.
Another aspect of the present invention relates to by detecting and/or the monitoring biomarkers thing detects method with monitoring of diseases or disorder (preferred diabetes), and biomarker includes but not limited to, GM, the human plasma and the urine protein of PTM and MA form.
On the other hand, the present invention relates to by utilizing multiple mensuration to determine the GM relevant with diabetes, PTM, and/or the combination of MA is so that the method for detection and monitoring of diseases or disorder (preferred diabetes).
Also in another invention, the present invention relates to by utilizing single mensuration to come simultaneously to determine the GM relevant with diabetes, PTM, and/or the combination of MA is so that the method for detection and monitoring of diseases or disorder (preferably diabetes).
In particular aspects of the present invention, GM, PTM and MA are present on the same gene prod and can be detected in the single analysis based on protein.
Also on the other hand, the several data that obtains from the multiple label according to the inventive method utilizes sorting algorithm further to assess so that determine health and diabetic disease states.
On the other hand, the biomarker according to the inventive method is associated with volume lifetime so that determine the longitudinal recording relevant with the prediabetes state with diabetes.
On the other hand specific, be associated with volume lifetime according to the biomarker of the inventive method and handle the longitudinal recording relevant with diabetes with treatment so that determine.
By will understand these and further other purpose of the present invention with reference to following detailed description and accompanying drawing.At that point, various references are all quoted in background parts and in describing in detail, and each is with reference to being hereby expressly incorporated by reference with its integral body.
Description of drawings
This patent document comprises at least one width of cloth color drawings.Filing a request and paying under the situation of required expense and will provide this patent copy by patent and trademark office with color drawings.
Fig. 1: analyze the deconvolution ESI mass spectrum coverage diagram that produces from the GcG of four individualities.The data that the mass spectrum representative is produced by the analysis that surpasses 100 individualities that is studied in the research process.Signal from three main allele products (Gc-1F, Gc-1S and Gc-2) and low frequency variation allele (variant) is instructed to.In addition to observing in the natural glycosylation at Δ m=+656Da place from its corresponding allele product (except Gc-2).Provide data so as to illustrate from the target of the GcG that is applied to the crowd from top to bottom (" top-down ") analyze the extent of information that produces.
Fig. 2: the GcG gene frequency of healthy (left column, n=50 individual) and T2DM (right row, n=52 individual).Monitor among the experimenter to observe Gc-1s at T2DM greater than about 5 times frequency.
Fig. 3: from the GcG mass spectrum coverage diagram (all are the Gc-1f/1f gene types) of three individualities: healthy (for red), T2DM (green) and id-T2DM (blueness) illustrate the saccharification GcG of the rising relevant with T2DM.Inset: standardization (normalized) is to being suitable for health (redness; N=50), T2DM (green; N=37) and id-T2DM (blueness; The box of the saccharification GcG of total GcG integral body n=15) must distribute by figure, and its mid point representative is from experimenter's mean value.After average, the diabetic is presented at 4-5 increase doubly in the relative saccharification.
Fig. 4: from the b2m mass spectrum coverage diagram of three individualities: healthy (be redness), T2DM (green) and id-T2DM (blueness) illustrate the saccharification level of the rising relevant with T2DM.Inset: be normalized into and be suitable for health (redness; N=50), T2DM (green; N=37) and id-T2DM (blueness; N=15) box of the saccharification b2m of total b2m (integrated signal) must distribute by figure (Box plot).After average, the diabetic shows because saccharification has 2-5 increase doubly on corresponding signal.
Fig. 5: from the cysC mass spectrum coverage diagram of the same sample that is used to produce Fig. 3 and Fig. 4.The saccharification that raises is designated as: for healthy (redness), T2DM (green) and id-T2DM (blueness).Inset: be normalized into health (redness; N=50), T2DM (green; N=37) and id-T2DM (blueness; N=15) box of the saccharification cysC of total cysC (integrated signal) must distribute by figure.After average, the diabetic shows because saccharification has 3-4 increase doubly on corresponding signal.
Fig. 6: from two individualities: the mass spectrum coverage diagram of the C-peptide of healthy (redness) and T2DM (green).With healthy individual (1.7%; MW=2819) compare, at T2DM individuality (8.1%; MW=2819) observe in and have obviously higher relatively des (GluAla) variant.Inset: box must be schemed the percentage composition of representative with respect to des (GluAla) the C-peptide of all isomeride that exist in sample.Mean value for healthy is 4.8%, and the mean value for T2DM is 9.3%.
Fig. 7: from the TTR mass spectrum coverage diagram of the same sample that is used to produce Fig. 5.The TTR sulfonation (with respect to the natural form of TTR) that raises is designated as: for healthy (redness), T2DM (green) and id-T2DM (blueness).Inset: for healthy (redness; N=50), T2DM (green; N=37) and id-T2DM (blueness; N=15), the TTR sulfonation must distribute by figure (Box plot) with respect to the ratio box of natural TTR.After average, diabetic's demonstration is compared with healthy individual about 10 times increase on the ratio of TTR sulfonation and natural TTR.
Fig. 8: the b2m in 102 people, the relative saccharification of cysC and GcG.The apart of 50 healthy samples (redness) and 15 id-T2DM samples (blueness) and 37 non--id-T2DM (green) is hinted that the protein glycation biomarker that is used in combination can be used for healthy population and T2DM patient are distinguished.Notice that GcG value and gene type are irrelevant.
Fig. 9: the shot chart-red point from the principal component analysis (PCA) of 102 data points shown in Fig. 9 is indicated healthy sample, Bluepoint indication ID-T2DM sample, and the non--ID-T2DM sample of green some indication.Principal ingredient 1 and 2 (describing at this) is made explanations to observe 94% variation in original data set, and is used to produce the model based on the SIMCA classification.
Figure 10: by GcG gene type and GcG saccharification overview to each data point of the individual single analysis generation of healthy (redness), T2DM (green) and id-T2DM (blueness).Shade dotted line representative does not have the shown 15/IS gene type of healthy control therefore not provide numerical value here as the expection reference levels of saccharification that are suitable for depending on gene type of T2DM indicator.Numeral (1-4) indication is suitable for the value of described individuality in this article.
Figure 11: the time supervision that utilizes a plurality of MA.Value of the corresponding saccharification of each label of three labels (saccharification/total x 100) and interior relative the describing of half life period (time in past) of body.The value that is connected by dotted line is the mean value that is suitable for health (square), T2DM (triangle of reversing) and id-T2DM (circle) experimenter that obtains.Individuality 1 (X ' s) prove to have relative good maintenance, especially several days before blood drawing with individual 2 (oblique lines forward).Individual 3 (oblique lines backward) and individual 4 (circles) be observed be displaced to his/her separately within the kind or outside, the more urgent or more treatment of standard of hint needs.Individual (5) prove to have good relatively maintenance through after the some months.
Figure 12 A-12D: from the Alb that healthy and T2DM patient's (oblique line forward) are got, ApoA1, the mass spectrum coverage diagram (as shown in the figure) of Apo C1 and TTR.Inset shows healthy (n=50) and T2DM (oblique line forward; N=52) oxidation number percent (when the ion signal integral body of saccharification is normalized into all kinds whole, every kind of protein being measured).
Figure 13: the MSIA mass spectrum of the C-peptide of being got from healthy and T2DM patient's (oblique line forward).
Figure 14: from positive ion MSIA mass spectrum healthy and the individual insulin of being got of T2DM patient's (oblique line forward).
Figure 15: recipient's operating characteristic (ROC) curve that is suitable for eight kinds of listed in the table 1 labels, comprise S-sulfonation TTR (S-sulfonation TTR), the APO C1 of oxidation (oblique line backward), the GcG of saccharification (triangle), the albumin (square) of the albumin of oxidation (triangle of reversing), saccharification, the CysC of saccharification (X ' s), the B2m (sinusoidal curve) of the haemoglobin of saccharification (circle), saccharification and the Apo Ai of oxidation (wave of point).
Figure 16: with saccharification and the figure that describes from the PC1 of saccharification (utilizing the PCA of the different saccharification values of the four kinds of protein to produce) oxidation that produces and the PC1 of oxidation (utilizing the PCA of observed different degree of oxidations in three kinds of protein to produce).T2DM body and function X indication.
Specific embodiment
One embodiment of the present of invention relate to new biomarker, include but not limited to Gc-globulin or GcG (also known), B2M (b2m) with protein in conjunction with vitamin D, cysteine proteinase inhibitor C (cysC), albumin (Albumin) and HemA﹠amp; B.
Mean the material that is used as the biological aspect indicator as for " biomarker ".As employed in this application, biomarker is to carry out him as the pharmacological reaction indicator that normal biological process, pathogenic course or treatment get involved to feel and measure and the characteristic of assessment.Particularly preferred biomarker by the present invention's expection is its material that detects indication specified disease or disturbance state, above-mentioned disease or disturbance state include but not limited to, diabetes, angiocardiopathy, crown and peripheral arterial disease, chronic obstructive pulmonary disease, apoplexy, cancer, senile dementia, neuropathy, retinopathy and deficiency disease; Above-mentioned is independent a kind of or as the common disease related with diabetes.The present invention expects also that indication is dangerous with disease or makes progress the relevant protein expression or the biomarker of state variation, or has the susceptibility of the disease of carrying out given treatment.
According to the present invention, biomarker can be genetic mutation (GM), translates the back and modifies (PTM) or metabolism change (MA).The biomarker of expection is finding (for example, blood plasma, serum, urine, saliva, tear, sweat or tissue extract in the detected gene prod from common coenocorrelation.Genetic mutation can include but not limited to, nucleotide polymorphisms, point mutation, haplotype, allelic variation and splicing variant.Translate the back modification and include but not limited to, about the enzyme and the non-enzyme variant of common or specific physiological gene prod.Metabolism changes and to include but not limited to, about the enzyme and the non-enzyme variant of the gene prod of disease Pathological Physiology.
The present invention also expects and is applicable to that detection and monitoring of diseases or disorderly data assessment measure and/or method, above-mentioned disease or disorder are not limited to, diabetes, angiocardiopathy, crown and peripheral arterial disease, chronic obstructive pulmonary disease, apoplexy, cancer, ALZheimer disease, neuropathy, retinopathy and deficiency disease; Above-mentioned independent a kind of or as the common disease related with diabetes.Preferably, the present invention relates to be applicable to data assessment mensuration and/or the method that detects and monitor diabetes.
Accordingly, another embodiment of the present invention relates to that biomarker detects and monitoring of diseases or disorderly method by detecting and/or measuring, and biomarker includes but not limited to, GM, the human plasma and the urine protein of PTM and MA form.The disease or the disorder that are detected and/or measured by the present invention are not limited to diabetes, angiocardiopathy, crown and peripheral arterial disease, chronic obstructive pulmonary disease, apoplexy, cancer, senile dementia, neuropathy, retinopathy and deficiency disease; Above-mentioned is independent a kind of or as the common disease related with diabetes.Preferably, the present invention relates to by detecting and/or measure GM, the method that the human plasma of PTM and MA form and urine protein biomarker detect and monitor diabetes.
Can comprise the gene prod analysis of conventional or unconventional form according to mensuration of the present invention; include but not limited to; Immunometeric (for example; enzyme linked immunosorbent assay (ELISA) (ELISA); radiommunoassay (RIA)), HPLC (high performance liquid chromatography) (HPLC), electrocapillary phoresis (CE); two-dimensional gel electrophoresis (2D-GE), the surperficial resonance of plasmid gene group (SPR) and mass spectrophotometry (MS) or its combination.
Data assessment method according to the present invention includes but not limited to, linear regression, the check weighing of heredity and dominance value and the assessment of non-check weighing, principal component analysis (PCA) (PCA), divide the soft independent modeling (SIMCSA) of analoglike and according to the assessment of time, such as the relation curve and the time relation curve (or protein half life period) of heredity and dominance value and morbid state.
Monitoring and diagnosis according to diabetes of the present invention include but not limited to, dangerous determinative and the label and the combination thereof of working.The detection of the present invention expection and diagnosis also comprise be used in combination multiple label so that correctly distinguish from healthy, prediabetes and diabetic disease states, and health, prediabetes or diabetic disease states and other disease are distinguished.
Comprise state or the progress of using the next clear and definite diabetes of one or more labels as for " monitoring " according to the present invention, and the reaction to treating.
In another embodiment, the present invention relates to utilize multiple mensuration to determine the GM relevant with diabetes, PTM, and/or the combination of MA is so that the method for detection and monitoring of diseases or disorder (preferred diabetes).
Also in another embodiment, the present invention relates to by utilizing single mensuration to come simultaneously to determine the GM relevant with diabetes, PTM, and/or the combination of MA is so that the method for detection and monitoring of diseases or disorder (preferably diabetes).
In certain embodiments of the invention, GM, PTM and MA are present on the same gene prod and are detected in the single analysis based on protein.
Also in another embodiment, the several data that obtains from the multiple label according to the inventive method utilizes sorting algorithm further to assess so that determine health and diabetic disease states.
In another embodiment, the biomarker according to the inventive method is associated with volume lifetime so that determine the longitudinal recording relevant with the prediabetes state with diabetes.
According to the present invention, utilize following method that T2DM is detected and monitors.This method comprises the following step that causes the specified protein in experimenter's body fluid to detect.Blood plasma, serum, urine, saliva, tear, sweat or tissue extract all are all examples of suitable body fluid.Begin from experimenter's collection of body fluids sample.In one embodiment, the body fluid sample of collection is a blood.After having gathered, body fluid is prepared to utilize electrospray ionization mass spectrum (ESI-MS) to carry out mass spectrometric immunoassay and is measured (MSIA).Be described in more detail in concrete preparation of being undertaken by the MSIA that adopts ESI-MS and the test example 2 below.
In another embodiment, after having gathered, body fluid is prepared to utilize matrix assisted laser desorption ionization flight time mass spectrum (MALDI-TOFMS) to carry out MSIA.Be described in more detail in concrete preparation of being undertaken by the MSIA that adopts MALDI-TOFMS and the test example 2 below.
Collection comprises GcG, b2m, cysC, Alb and Hem A﹠amp at the result who is provided by specific mass spectrometer of saccharification label; B.In addition, collect the result who provides by specific mass spectrometer, comprise albumin (Alb), aPoA 1 (Apo A1), apoC 1 (Apo C1) and prealbumin (TTR) at the oxidation label of emphasis.In addition, collect the result who provides by specific mass spectrometer at two kinds of enzyme signal tracers that comprise C-peptide (C-pep) and insulin.
Saccharification label in T2DM experimenter is with the positive mass shift that himself shows as with respect to the MS result of health volunteer's target protein.Be described in more detail in this example 4 below.Concrete, at b2m, cysC, GcG, Alb and Xue HongdanbaiA ﹠amp; B chain ((Hem A﹠amp; B, a kind of composition wherein is HbA1c) the middle ratio rising of finding saccharification.
Emphasis oxidation label in T2DM experimenter is with the positive mass shift that himself shows as with respect to the MS result of health volunteer's target protein.Be described in more detail in this example 8 below.Concrete, at the high-density lipoprotein (HDL) composition Apo A1 that selects, Apo C1 and TTR are different with discovery degree of oxidation among the Alb.
Enzyme labeling thing in T2DM experimenter (being specially C-peptide and insulin) is with the negative mass shift that himself shows as with respect to the MS result of health volunteer's target protein, and wherein some protein is blocked.Be described in more detail in this example 7 below.Concrete, in T2DM experimenter, observe the variant that blocks of C-pep and insulin with higher probability with higher frequency.
Utilize the initial single argument of recipient's operating characteristic (ROC) and the multivariate of all data of the soft independent modeling (SIMCSA) that utilizes principal component analysis (PCA) (PCA) and branch analoglike to cause the health volunteer is separated with the experimenter fairway of suffering from T2DM.These data can be used for monitoring the path from health to T2DM in particular subject.These data also can be used for providing for the experimenter retrospective analysis of saccharification level a few days ago in addition.
By following limiting examples the present invention is further explained.
Example 1
The experimenter who suffers from disease: health, diabetes B (T2DM) and depend on insulin type Diabetes B (the id of type T2DM)
Provide below by to (not knowing to suffer from disease by healthy individual; N=50), the T2DM individuality (is diagnosed as T2DM and passes through control usual diet, exercise and non-insulin drug therapy; N=37) and the id-T2DM individuality (depend on insulin, be diagnosed as T2DM and treat by applying insulin; N=15) crowd carries out genetic mutation that primary election obtains, translates the example that the back is modified and metabolism changes.From fasting these individualities after 8 hours, gather EDTA-plasma sample (agreeing and approval IRB), and store up to utilizing following method to analyze down at-70 ℃ through informing.Also obtain the record of sex, race, BMI, medication history and current treatment from each diabetic.
Example 2
Crowd's proteomics and T2DM
Table 1 illustrates 15 kinds of blood and carries label (Dan Baizhi ﹠amp; Protein variants) exemplary list, each can both distinguish healthy and T2DM experimenter.The important label that should be noted that is owing to cause with the relative regulation and control of the known PTM that affected physiology path is relevant in T2DM diagnosis or treatment.
Figure BPA00001256415000141
Figure BPA00001256415000151
HbM SIA detects (+162Da) the saccharification of the 2nd PTM of HbA1c and haemoglobin B-chain (at+120Da place) and A-chain.Detect degree of oxidation difference with natural form with respect to the consume of all variant forms halfcystineization of+119Da place (for example).Also utilize this mensuration monitoring (simultaneously) saccharification difference.Oxidation difference is the sulfonation (+80Da) increase that takes place at the cys10 place.(+16Da extremely+48Da) locates to take place oxidation at methionine.Number percent reflects total oxidability.Apo C1 has two kinds of forms, and is complete and block at n terminal Thrpro place.The C-peptide locates to block at n terminal glutamic acid alanine (GluAla)-be called C-peptide (3-31).Insulin is located to block at c-terminal Thr (b-chain).This measures the mass shift of also agreeing to detect insulin formula, for example, and Lantus and Novolog.
In the observation hurdle of table 1, the number percent of mark is the measured value of the concrete kind for each protein.B2M is measured a kind of corresponding saccharification of form.Cysteine proteinase inhibitor C (cysC) is measured a kind of corresponding saccharification of form.GcG measures a kind of corresponding saccharification of form and three kinds of haplotypes of the genotype data that is associated with T2DM.Albumin is measured the corresponding saccharification of two kinds of forms and a kind of oxidation halfcystineization of form.Xue HongdanbaiA ﹠amp; B measures a kind of corresponding oxidation of hemoglobin A of form and the haemoglobin B-chain of two kinds of forms.TTR measures the corresponding oxidation of two kinds of forms.Apo C1 measures the corresponding oxidation of two kinds of forms.The C-peptide is measured the corresponding of two kinds of forms and is blocked des (E) and des (EA).Insulin is measured a kind of the corresponding of inherent insulin of form and is blocked, the administration form of b-chain des (30) and Lantus and Novolog and the relative distribution of clipped form thereof.
These researchs are carried out the experimenter who is made of 50 healthy individual (not knowing to suffer from disease) and 52 T2DM patients (comprise that 37 are diagnosed as T2DM and the patient by controlling usual diet, exercise and non-insulin drug therapy and 15 and depend on insulin, be diagnosed as T2DM and by applying the patient that insulin is treated).From fasting these individualities after 8 hours, gather the EDTA-plasma sample, and store up to utilizing following method to analyze down at-70 ℃.Also obtain the record of sex, race, BMI, medication history and current treatment from each diabetic.
The following electrospray ionization mass spectrum (ESI-MS) that utilizes carries out mass spectrometric immunoassay mensuration (MSIA).Human plasma sample (125 μ L) is diluted twice and be placed in the titer plate of 96 containers in HEPES buffer salt (HBS).The automatic control control system that extraction imbibition tip is equipped with in utilization extracts protein (and variant) (preparing with the anti-people's polyclone of rabbit lgG according to the protein of selecting).After extraction, the protein of clear and definite combination is by use HBS, water, 2M ammonium acetate/acetonitrile (3: 1v/v) flushing and removing, and then wash.Then be drawn in the tip (covering the solid support thing) residual protein is carried out elution, after passing through the short time (~30 seconds), the protein of elution is discharged in the container of clean titer plate by formic acid/acetonitrile/water (9/5/1v/v/v) with 5 μ L.Be that ESI-MS prepares then with eluant dilute with water twice.Usually, 24 samples are carried out parallel processing (be not with whole 96) so that the day output of coupling LC/ESI-MS.Utilize Bruker microTOFq and Eksigent nanolC *The HPLC binding operation of 1D lazy flow is carried out mass spectroscopy.Analyzing use for these catches and the concentration of specimens/solvent exchange of dilute form rather than traditional LC.Extract pattern with the sample injection of 5 microlitres and by Eksigent nanolC by Spark Holland Endurance self-actuated sampler with microlitre *1D is loaded into protein cap grabber with 10 μ L/min (90/10 water/acetonitrile comprises 0.1% formic acid, solvent orange 2 A), and (Michrom Bioresources, Aubum CA) (are configured to non-directly mobile on the switching valve of 6 ports).After 2 minutes, change automatically the switching valve position, and the flowing velocity on cap grabber filter cylinder becomes the 1 μ L/min (flowing directly to the ESI inlet) of solvent orange 2 A, and the solvent orange 2 A of 1 μ L/min tilts to become in 8 minutes the 10/90 water/acetonitrile solution that comprises 0.1% formic acid immediately.10.2 end of run after minute, and 100% solvent orange 2 A flows back to.By making all ions monitor the ion flight time so that only obtain data with the TOF pattern by the quadruple stage (not having chosen in advance) of mass spectroscopy instrument and with the scope (under 5kHZ, taking a sample) of 500-3000m/z.The about 1.5 minutes wave spectrum of record through the chromatogram summit of protein extraction thing is averaged.On the either side of any crest of deconvolution, utilize BrukerDaltonics DataAnalysis v3.4 software that the envelope of ESI state of saturation is carried out the mass range of deconvolution to 1000Da.The wave spectrum of deconvolution carries out baseline and removes and all crests are integrated.
Utilize matrix assisted laser desorption ionization flight time mass spectrum (MALDI-TOFMS) to carry out MSIA.The automatic control control system that extraction imbibition tip is equipped with in utilization according to protein of interest matter extracts protein and variant (lgG derives with the anti-people's polyclone of rabbit).After extraction, the protein of clear and definite combination is by use HBS, water, 2M ammonium acetate/acetonitrile (3: 1v/v) flushing and removing, and then wash.Then by matrix solution (2: 1v/v with 5 μ L, water: with the saturated ACN of Sinapinic acid that adds 0.4%TFA) be drawn in the tip (covering the solid support thing) residual protein is carried out elution, and matrix/protein mixture is deposited on the surface into normalized 96 containers of MALDI-TOFMS target.Utilize Bruker Autoflex III to carry out mass spectroscopy with the laser repetition rate (Nd:YAG) that postpones extraction linear model and 200HZ.By suing for peace and acquisition wave spectrum (2,500 laser radiation) at 25X 100 laser radiations (each satisfies the standard of S/N>10 and discrimination rate (FWHM)>1, the 000) wave spectrum that the diverse location in the sample preparation is got.Signal integration (with respect to baseline) by baseline removal and each signal of interest is subsequently handled wave spectrum.For each individuality, be normalized into the protein of form of ownership of discovery by variant form integral body and the analog value of definitive variation body (ion signal) with protein.
Example 3
Gc-globulin (being also referred to as protein) in conjunction with vitamin D: genetic mutation and translate after Modify
Gc-globulin or GcG (also known with the protein in conjunction with vitamin D) have the plasma proteins of nominal molecular weight for~51kDa, and its estimated concentration in blood plasma is at 200-600mg/L.It is known in and has three kinds of high-frequency allelic variation bodies, Gc-1F, Gc-1S and Gc-2 and other low-frequency variant among the crowd.For GcG, main physiology role comprises the transmission of vitamin D metabolin, fatty acid transmission, actin chelation and macrophage activation effect.The variation of this protein can constitute Widesweeping result's physiological event like this.
In research process, utilize the immunoassays extraction to measure (ESI-MS) through electrospray ionization mass spectrum afterwards and from blood plasma, gene and dominance variance body are analyzed.Human plasma sample (125 μ L) is diluted twice and be placed in the titer plate of 96-container in HEPES buffer salt (HBS).The automatic control control system that extraction imbibition tip is equipped with in utilization extracts GcG (and variant) (with the anti-people GcG of rabbit polyclone lgG preparation).After extraction, the protein of clear and definite combination is by use HBS, water, 2M ammonium acetate/acetonitrile (3: 1v/v) flushing and removing, and then wash.Then be drawn in the tip (covering the solid support thing) residual protein is carried out elution, after passing through the short time (~30 seconds), the protein of elution is discharged in the container of clean titer plate by formic acid/acetonitrile/water (9/5/1v/v/v) with 5 μ L.Be that ESI-MS prepares then with eluant dilute with water twice.Usually, 24 samples are carried out parallel processing (be not with whole 96) so that the day output of coupling ESI-MS.Utilize Bruker microTOFq and Eksigent nanolC *The HPLC binding operation of 1D lazy flow is carried out mass spectroscopy.Analyzing use for these catches and the concentration of specimens/solvent exchange of dilute form rather than traditional LC.Extract pattern with the sample injection of 5 microlitres and by Eksigent nanolC by Spark HollandEndurance self-actuated sampler with microlitre *1D is loaded into protein cap grabber with 10 μ L/min (90/10 water/acetonitrile comprises 0.1% formic acid, solvent orange 2 A), and (Michrom Bioresources, Aubum CA) (are configured to non-directly mobile on the switching valve of 6 ports).After 2 minutes, change automatically the switching valve position, and the flowing velocity on cap grabber filter cylinder becomes the 1 μ L/min (flowing directly to the ESI inlet) of solvent orange 2 A, and the solvent orange 2 A of 1 μ L/min tilts to become in 8 minutes the 10/90 water/acetonitrile solution that comprises 0.1% formic acid immediately.10.2 end of run after minute, and 100% solvent orange 2 A flows back to.By making all ions monitor the ion flight time so that only obtain data with the TOF pattern by the quadruple stage (not having chosen in advance) of mass spectroscopy instrument and with the scope (under 5kHZ, taking a sample) of 500-3000m/z.The about 1.5 minutes wave spectrum of record through the chromatogram summit of GcG extract is averaged.On the either side of any crest of deconvolution, utilize Bruker Daltonics DataAnalysis v3.4 software that the envelope of ESI state of saturation is carried out the mass range that deconvolution is incorporated into 1000Da.The wave spectrum that deconvolution is closed carries out baseline and removes and all crests are integrated.The mass spectrum crest area of formization is transferred to spreadsheet so that corresponding crest density (Peak abundance) is further calculated and determined.
Fig. 1 illustrates from the GcG of four individualities and analyzes the overlapping ESI mass spectrum coverage diagram that closes that produces, and provides it so that the extent of information that is caused by single mensuration is shown.For three kinds usually in research process observed homozygous gene carry out signal and observe.Gc-1F (MW is shown Calc=51188.2), Gc-1S (MW Calc=51202.2) and Gc-2 (MW Calc=51215.3Da).The quality of determining (for all samples of analyzing in this mode) is in the 2Da of calculated value.The heterozygosis that in research process, is these three types of genes combination with observed other three types the gene of high-frequency, just, Gc-1F/1S, Gc-1F/2, and Gc-1S/2.But in research process, postback existing other genotypic variant sometimes, in research process, in Population, occur with low frequency.Variant after indication is translated in addition, i.e. the saccharification [(NeuAc) 1 (Gal) 1 (GalNac) 1disaccharides] of O-link.Attention saccharification signal is being observed under identical mass shift with respect to the gene of Gc-1F and Gc-1S type, rather than the gene of Gc-2 type.This observed phenomenon lacks the consistent (Thr of GcG-2 type gene that O-links the saccharification optimum position with being derived from 420Be converted to Lys 420).Only, in T2DM experimenter, mainly find Gc-1S allele (Gc-1S/1S, the gene of Gc-1F/1S and Gc-1S/2 type) to after the genotype data assessment from all experimenters (n=102 individual).As shown in Figure 2, with respect to the health volunteer, allelic frequency increase~500%[Chi-square test in T2DM experimenter: (2 sample donor type x3 main GcG allele; α=0.01; The degree of freedom of 2 degree; X2=49.6, p<0.0001; CramerV=0.474)].
There is genetic mutation (GM) in this example proof and translates the back and modify (PTM) in being derived from the product of term single gene, and has proved the ability of utilizing single analysis (just, with single analytical model) to determine this variation simultaneously.
Example 4
Gc-globulin (being also referred to as the protein in conjunction with vitamin D): metabolism changes
Unique advantage based on protein analysis is the ability of comparing by the additional data that obtains based on nucleic acid determination for not.As shown in fig. 1, utilizing the ESI-MS mensuration of target is possible to carrying out further signature analysis about the GcG that shifts the back variation.Should be noted that and depend on individuality, locate can be observed range protein phenotype such as natural saccharification (translating the back modifies) in different relative intensity (reaction of their relative quantity).This identical method can be used for screening the change about variation and metabolism after the transfer of the Pathological Physiology of T2DM, just the saccharification variant of GcG.Fig. 3 illustrates the GcG mass spectrum coverage diagram (all are the Gc-1f/1f gene types) from three individualities: healthy (for red), T2DM (green) and id-T2DM (blueness).Signal level at the 162Da place in the mass spectrum that is derived from the individuality of suffering from T2DM increases, and the quality of mass ratio nature GcG is big.This skew expection corresponding to above-mentioned molecular weight causes by increasing the 1-deoxyfructosyl adduct, and it is consistent with the blood sugar level rising about T2DM.Observe to organize, the average level of the saccharification GcG in T2DM experimenter (integration ion signal) is the average level high approximately 4-5 times (referring to the inset of Fig. 3) than the saccharification GcG that finds in healthy individual.
There is the change (MA) of genetic mutation (GM) and metabolism in this example proof in being derived from the product of term single gene, and has proved and utilize single analysis (just, with single analytical model) to analyze their ability simultaneously.
Example 5
B2M and cystatin C: metabolism changes
In continuous screening based on the crowd, two kinds of other glycated variants of plasma proteins are found to occur with the level that raises in T2DM experimenter, and these two kinds other the glycated variants of plasma proteins are B2M (b2m) (light chain of the main histocompatbility compound body of the first kind that exists with about 1mg/L in blood plasma usually) and cysteine proteinase inhibitor C (cysC) (cystatin that exists with about 0.1mg/L in blood plasma usually).Extract b2m simultaneously in the same sample that the extraction imbibition tip of the polyclone lgG preparation of mensuration by utilizing anti-people b2m of rabbit and cysC uses and cysC carries out from GcG measures.After extraction, the protein of clear and definite combination is by use HBS, water, 2M ammonium acetate/acetonitrile (3: 1v/v) flushing and removing, and then wash.Then by matrix solution (2: 1v/v with 5 μ L, water: with the saturated ACN of Sinapinic acid that adds 0.4%TFA) be drawn in the tip (covering the solid support thing) residual protein is carried out elution, and matrix/protein mixture is deposited on the surface into normalized 96 containers of MALDI-TOFMS target.Utilize Bruker AutoflexIII to carry out mass spectroscopy with the laser repetition rate (Nd:YAG) that postpones extraction linear model and 200HZ.By suing for peace and acquisition wave spectrum (2,500 laser radiation) at 25X 100 laser radiations (each satisfies the standard of S/N>10 and discrimination rate (FWHM)>1, the 000) wave spectrum that the diverse location in the sample preparation is got.Signal integration (with respect to baseline) by baseline removal and each signal of interest is subsequently handled wave spectrum.For each individuality, the protein that is normalized into the form of ownership of discovery by glycosylated form (b2m or the cysC) integral body with protein is determined relative saccharification value (ion signal).
Fig. 4 illustrates the b2m mass spectrum coverage diagram from three people: healthy (for red), T2DM (green) and id-T2DM (blueness).Identical with all wave spectrums is because the b2m of wild type (m/z=11,730Da) and the signal (sinapic acid of matrix additive; At m/z=11,936﹠amp; 11, the signal of 954Da) locating.With the GcG analysis classes seemingly, in the mass spectrum that is derived from the individuality of suffering from T2DM, find increasing of saccharification level, indicate than b2m is big on molecular weight by signal at the 162Da place.Observe to organize, the level (with respect to ion signal) of the saccharification b2m in T2DM experimenter is the level high approximately 2-5 times (referring to the inset of Fig. 4) than the saccharification b2m that finds in healthy individual.
In the cysC screening, obtain similar result.Fig. 5 illustrates the cysC of the same sample generation of using and the mass spectrum coverage diagram of variant in GcG and b2m analysis.Identical with all spectrograms (Profile) is the signal of four kinds of form cysC: N-terminal desSSP (m/z=13,073Da), N-terminal desS (m/z=13257/13273, respectively under the situation that does not have and have hydroxyproline), cysC (the m/z=13 of nature, 344) and hydroxyproline cysC (m/z=13360), add the addition product and the cysC (m/z=13550-13584) of wild type.In addition, in the diabetic, found the signal of saccharification cysC (m/z=13509 and 13525).For GcG and b2m, the mean value that three experimenters are determined demonstrates about 3-4 corresponding increase (seeing Fig. 5 inset) doubly on the saccharification signal from T2DM experimenter.
This example proof utilizes single analysis to determine to be derived from the ability of the various ways product of a plurality of genes simultaneously, and it comprises the change (MA) with the metabolism of disease association.This example also proves the multicomponent mensuration that can analyze simultaneously more than a kind of MA of and disease association.
Example 6
C-peptide: translate the back and modify
In this research, utilization is similar to those methods of using the C-peptide is carried out in the blood plasma of example 1 quantitatively and semi-quantitative analysis in example 2-4.Fig. 6 illustrates by healthy individual and suffers from the individual wave spectrum that obtains of T2DM.More interesting, the variant of the previous C-peptide of not reporting of the elevated levels that existence is compared with healthy individual in T2DM patient is defined as des (Glu-Ala) isomeride, thereby is established as the new candidate's of the PTM form that is suitable for T2DM biomarker.Intention is not subjected to the restriction of any specific mechanism, it is believed that two peptide protease IV (DPP-IV, CD26, EC 3.4.14.5) give the credit to this specific cleavage product, and its physiopathologic research with ongoing T2DM is consistent.This multi-functional transmembrane serine protease can be given the credit to the version that the Glu-Ala of the C-peptide of extensively seeing blocks in this research, above-mentioned is because above-mentioned enzyme spcificity ground is opened Xaa-Pro or Xaa-Ala from the amido end check of peptide hormone.Consider this, modified forms is effective biomarker in the T2DM clinical diagnosis and the biologically active that DPP-IV is shown after this specific the translating that rolls up confirmation C-peptide that corresponding des (Glu-Ala) the C-peptide in the T2DM individuality is compared with healthy individual.
This example proof with the protein of PTM and MA form or gene prod as with the direct label of the enzymatic activity of disease association.
Example 7
The enzyme signal
Saccharification and oxidative stress are positive mass shift with respect to target protein with their oneself expressions.According to the present invention, the mass shift that existence is born in about some protein of T2DM-just, block.Concise and to the point, (reflective) MALDI-TOFMS MSIA that will be suitable for C-peptide (C-pep) and insulin (Ins) measures and is studied to be used for research described herein.After in individuality, initially screening, the variant that blocks of C-peptide, insulin and insulin analog is discerned and observed so that be associated with T2DM experimenter.Figure 13 illustrates the negative ion MSIA wave spectrum of quantitative representative by those contents of the individuality acquisition of checking in this research.In wave spectrum, observe other two kinds of signals at the isotopic complete C-peptide signal of the list of m/z=3017.50Da and m/z=2888.49Da and 2817.45Da place record.Finish with the precision of 10ppm and by the portion gene sequential analysis that utilizes MALDI-TOF/TOFMS, these signals are defined as the C-peptide respectively, C-pep (2-31) and C-pep (3-31).Generally in healthy and T2DM experimenter, observe this three kinds of signals.(health female) finds the heterozygous mutant point of a C-peptide Ala 18Glu in above-mentioned experimenter.Be normalized into from the overall signal of all species and to carrying out relative quantitative test by ion signal from each individual spectral data with each different basis weights species.Then by will be in their corresponding experimenters and the corresponding ion signal of each species is assessed with respect to the existence of T2DM from the packet of individuality.C-peptide (2-31) demonstrates few difference between health and T2DM experimenter.But, find that there is sizable difference in being distributed in relatively between two experimenters of C-peptide (3-31).Figure 13 inset illustrates for the histogram relatively of the frequency of occurrences between two experimenters of the corresponding ion signal of C-peptide (3-31).Approximately average (the averaging in all individualities in the experimenter) 9.0% of wide region observe to(for) T2DM experimenter distributes, and observes approximately average 4.8% narrow range distribution for the health volunteer by contrast.Oblique line forward is the MSIA wave spectrum from the C-peptide of healthy and T2DM.Find as one man in two experimenters as can be seen that in Figure 13 two kinds of n-ends block variant, C-pep (2-31) and C-pep (3-31).In T2DM experimenter, observe C-pep (3-31) (referring to the inset of Figure 13) with higher relative probability with higher frequency.
On the experimenter, also carry out insulin MSIA.Two exemplary wave spectrums that T2DM patient from healthy individual and insulin-dependent shown in Figure 14 (oblique line forward) is got.At m/z Ave=5,808.4Da has found at the place that complete endogenous insulin is so that regulate and control in two individualities.In addition, (according to his medical treatment record) found the insulin homolog (insulin glargine as the Lantus of independent signal in the T2DM individuality; Mw=6,063.7) and Novolog (insulin aspart; Mw=5831.6).Handling according to known physiology, find initial removal by two kinds of C-terminal arginine residues, then is secondary Thr residue (from the C-end of b-chain) and observe the Lantus degraded.But do not observe the degradation products with the Nololog sequence alignment, endogenous insulin variant is defined as the C-end residue (Des (B30) HI) of the b-chain that (in all experimenters) block.Be similar to C-pep (3-31), in T2DM experimenter, have (referring to the inset of Figure 14) with high relatively distribution and frequency.
Example 8
Transthyretin (being also referred to as prealbumin or TTR): translate the back and modify body
Mode with the aforesaid way that is similar to b2m and cysC is carried out the target analysis of complete TTR in health volunteer, T2DM experimenter and id-T2DM experimenter.Fig. 7 illustrates the mass spectrogram for the TTR of several Different Variation forms from healthy individual, T2DM patient and id-T2DM patient, mainly be: natural TTR (m/z 13762), the TTR of sulfonation (m/z 13842), the TTR of halfcystineization (m/z 13881) and Cysteinylglycyl TTR (m/z 13938).As shown in inset, find that the ratio of sulfonation TTR and natural TTR demonstrates bigger increase in the plasma sample from the diabetic.So, sulfonation TTR becomes the aid mark thing of TZDM by the common degree of the inflammation/oxidative stress of indicating body one by one and standing in several days in the past.
To be similar to the mode of protein glycation, in multiple proteins, find different oxidations.Figure 12 A to Figure 12 D illustrates healthy individual (n=50) and T2DM (oblique line forward; N=52) oxidation number percent (when the ion signal integral body of saccharification is normalized into all species whole, every kind of protein being measured).Figure 12 A illustrates the mass spectrum coverage diagram of the albumin (AlB) of taking from healthy individual and T2DM (oblique line forward) individuality, Figure 12 B illustrates the mass spectrum coverage diagram of aPoA 1 (Apo A1), and Figure 12 C illustrates the mass spectrum coverage diagram of apoC 1 (Apo C1) and the mass spectrum coverage diagram that Figure 12 D illustrates prealbumin (TTR).Albumin and TTR demonstrate respectively with the form of halfcystineization (dm=119Da) and sulfonation (dm=80Da) the different degree of oxidation (also observed because different saccharification signals in the albumin wave spectrum) at its free halfcystine place.The oxidation of apolipoprotein is mainly sentenced the sulfoxide form at free methionine (three kinds are Apo A1 and a kind of APO C1 of being) is taken place.Because therefore the blocking of two n-terminal amino acids from complete species also find signal in Apo C1.This example proof is used as the protein of PTM form the auxiliary biomarker of T2DM.
Example 9
Metabolism changes data: healthy classification model construction to T2DM
Analyze with above-mentioned mensuration at the individuality described in the example 1.Be suitable for GcG, the omen of the MA of b2m and cysC illustrates with three dimensions healthy individual and T2DM individuality is distinguished (Fig. 8).Above-mentioned differentiation hint is after carrying out suitable training, and the supervised classification technology can provide the effective means to these three kinds of normal saccharification of protein definition " space " (by the ellipse indication), and it can be used as baseline so that distinguish the unusual saccharification that is associated together with T2DM.At that point, the purpose of classifying for the soft independent modeling (SIMCSA) that generates minute analoglike from the data of healthy sample (the red point among Fig. 8) is carried out principal component analysis (PCA) (the PCA) (software that utilization is purchased: The Unscrambler; CamoSoftware, Inc., Woodbridge, NJ).
Fig. 9 illustrates the shot chart of this PCA.Concise and to the point, from health volunteer's (n=50 individuality; Each individual three data value) data with full cross validation and standardized variable variance (just, three saccharification values are administered to model with equal weight) so that set up the model of health data.Then model is used from the challenge of all experimenters' (n=102) data so that set up the practicality that it distinguishes healthy individual and T2DM individuality.Utilize this model under the favourable level with p<0.001, it is unhealthy that in 50 healthy samples three are classified as, and in 52 T2DM samples two are classified as and are respectively 96% clinical susceptibility and 94% specificity on health-tolerance.Should be noted that mensuration is quite important for three wrongheaded discriminations, hint that these individualities may be and unwitting real diabetic-just, American 1/3rd part does not know that they suffer from diabetes.About misjudgment, should be noted that T2DM has a kind of disease that is in " gray area " between health and the T2DM, is commonly referred to prediabetes.In case be diagnosed as diabetes, obtaining this diabetes boundary line state is the real purpose that is used for the treatment of.Therefore, the soluble above-mentioned two kinds of misjudgments of the good processing of T2DM.
Generally speaking, the analysis based on SIMCA of three kinds of glycated proteins demonstrates the important leverage that is used for determining and monitoring T2DM, and representative is suitable for the mensuration that maintains the leading position of bigger challenge project.In addition, it carries out improved technical foundation as adding other label (in case they are found).In order correctly to estimate, it should be noted that the present invention is not by utilizing multivariate analysis so that the spectral data of determining with non-determined value that comprises of scrutiny larger volume begins for improved this kind addition method of biomarker.On the contrary, only add from definite formal protein demonstration and serve as a mark the data of guarantee of thing (the relative saccharification value of plasma proteins in this case) so that analyze.In this mode, the value of independent (independence) label can be used as the part of whole analysis and assesses.For example, utilize all three kinds of decisions to obtain above-mentioned false judgment rate and negative ratio (being respectively 6% and 4%).These tolerance are through utilizing two kinds of improvement that protein carries out just now, for example, only using b2m and GcG data to cause occupying deputy false judgment rate and negative ratio (being respectively 8% and 12%).If oppositely observe, nugatory label can be got rid of from analyze.This method of " foundation " multivariate analysis is opposite with the example of clinical proteomics, consider abundant non-target spectral data in the clinical proteomics, most data are unessential for prediction, and in the worst case since the illusion of data set (64,65) lead to errors.Therefore, by the value of unreasonable (or wrong) is removed from measure, the present invention's expection makes full use of data and appraisal procedure so that disease is correctly classified.
This example proof utilizes a plurality of values of MA and PCA or classification model construction correctly healthy individual to detect from the disease individuality and be diagnosed.
Example 10
The genotype of single mensuration: GcG and saccharification
The advantage that the GcG that carries out based on MS measures is can single mensuration to obtain genotype and albumen dominance (saccharification) data-each tolerance to be had independently at T2DM and detects and the value of monitoring.The single assay determination that does not at present also have to produce equal data.For example utilize current technology, can under nucleic acid level, for example utilize single nucleotide polymorphism (SNPs) analysis or gene sequencing to carry out the GcG Genotyping.Like this, the analysis of the GcG of these three kinds of main allelic forms will need at least two kinds of two kinds of SNP can be identified as owing to genotypic mensuration based on gene.Data from this Genotyping will combine with the saccharification data, and its mensuration has a little not simple and direct.Be similar to HbA1c, for T2DM detected and monitors, the corresponding abundant intensity of measuring the GcG of glycosylated form also was important.This measurement will need at least two kinds of mensuration (for example, based on the immune measurement method of protein), and a kind of is GcG (denominator) to form of ownership, and second kind of mensuration can be discerned all saccharification GcG (molecule).Must carry out at least four kinds of mensuration generally.Can propose other analytical plan, but in all cases, must carry out a plurality of mensuration so that produce and be equivalent to the data of measuring based on MS.
The present invention recognizes GcG Genotyping (GM) and saccharification (MA) is used in combination.Figure 10 illustrates the result that two kinds of tolerance combine and use.Do in upward execution of given individuality [healthy (redness), T2DM (green) and id-T2DM (blueness)] from the every bit of each analysis.What limit on the X-axis is six oligogene types of GcG.What provide on the Y-axis is the relative abundant intensity of the saccharification GcG that finds in individuality.Provide by the highlighted dotted line of gray area so as the function of saccharification GcG (relative) with the GcG gene type with healthy individual best distinguishing from T2DM, and the scope that defines the individuality that can indicate abundant processing T2DM (or early stage T2DM).Except several exceptional values, there is the above-mentioned threshold value of the saccharification GcG level of the indication T2DM that depends on gene type.The prospect that the dominance of the protein of this kind (single analysis) gene type is measured is important.This mensuration himself is worth by following performance: 1) indication develops into the possibility of T2DM; 2) detect T2DM, and 3) progress (and/or result of treatment) of monitoring T2DM on personalized level.Reference is data shown in figure 2, but the X-axle self be illustrated as based on Genotyping be suitable for T2DM pre-aligned-just, measure a people can develop into T2DM in its life gene risk factor, carrying the Gc-1S gene type will easier trouble T2DM.The threshold value that depends on gene type (as the indicator of T2DM) that is suitable for saccharification produces more personalized mensuration, and its existence based on the pathologic, physiologic label of initial risk factor and T2DM distinguishes individuality-just be used in combination two values so that more accurately point out when individual development becomes T2DM and him for the reaction for the treatment of from general crowd.This differentiation is the basis of personalized medicine.
GM and MA that this example proof will be derived from single analysis are used in combination so that determine disease.This single mensuration and data assessment method can be indicating predetermined position, beginning, progress and to the reaction for the treatment of diabetes.
Example 11
Multi-tracer: depend on the assessment of time
Purposes from a specific novelty of the data of different glycated proteins (MA) is to observe individual blood sugar level (by the saccharification level of three kinds of protein) as the function of time, and momentary fluctuation can be observed by relevant with the protein volume lifetime.Except the more accurate diagnosis of tangible T2DM, at this interested other theme in order to determine T2DM " gray shade " in early stage more accurately, in case and made a definite diagnosis the maintenance of back monitoring T2DM individuality for it.It is believed that individuality can advance T2DM early stage or be offset out T2DM early stage (or keeping well) (at once or in the past about 90 days) at the time point bias internal that utilizes the monitoring of current label.When body one by one diagnosed T2DM originally screening is fallen the time (for example, the low FGT test of carrying out owing to a large amount of rapid screening before the test (OGTT of no use or HbA1c)) above-mentioned effect reading that can lead to errors potentially.For the individuality that is diagnosed as T2DM, the unnecessary change that can relatively keep authenticity (for example, interim skip treatment or before the fasting glucose test not enough on an empty stomach those) to cause potentially treating.Reflect that the polynary mensuration of different time points in the individual time in the past can provide some benefits about these problems.
Figure 11 is illustrated in the possibility of " the half life period clock " of setting up momentary fluctuation in the range protein saccharification.The figure of relative saccharification to the time before taking a sample is shown.The volume lifetime of label is for b2m, cysC, GcG, AlB, Hem (A﹠amp; B) be respectively about 0.5,2,85,550 and 2000 hours.Colored dotted line will link for the mean value of the glycated proteins found in healthy (triangle of reversing) and T2DM (square) experimenter's analytic process.The data of five individualities of in Figure 16, indicating in addition that provide.For five individualities, all labels all are lower than corresponding experimenter's mean value, represent abundant and controlled non-treatment based on insulin.Individual 4 present the data drawing list that is roughly the same, except saccharification in the nearest time in the past raises (and with reference to Figure 16, also presenting high relatively oxidative stress value).Under another kind of extreme value, individual 1 does not correctly treat, and perhaps treatment itself is incorrect.Similarly, in 1-2 in the past month, individual 2 present the saccharification that (extreme value) raises, but saccharification begins to be reduced to low relatively level in several weeks in the past.For the individuality 3 that before was not diagnosed as T2DM, find to be displaced within the T2DM level or outside, as the example of baseline, perhaps be " T2DM in earlier stage " state.At last, should be noted that individuality 3,4 and 5 all is rendered as the diastatic index that is roughly the same when the haemoglobin that utilizes saccharification is measured, but arrive in the time of drawing blood along different paths.
These labels that depend on the time allow based on the analysis of single plasma sample the glycosylation status of individuality to be observed in detail.As monitoring tool, multipoint images provides the detail drawing of the individuality of keeping T2DM, and it is the form of personalized medicine, at this individuality is carried out with respect to his long term monitoring own.The multiple spot instantaneous imaging of healthy saccharification be as may solving the necessary baseline of high risk individuality (T2DM early stage), this it is believed that individuality can be displaced within the T2DM state or outside.At last, monitor short-term and long-term saccharification simultaneously, too drastic about " right and wrong and be glucose " its oxidation that stress disease with respect to hyperglycaemia causes is interesting relatively.
This example proof is utilized multiple MA to observe as the disease of the function of time and is handled.
Example 12
Single argument is measured and multidimensional analysis
Utilize recipient's operating characteristic (ROC) curve that each saccharification and the too drastic label of oxidation are assessed, its reflection label distinguishes healthy individual by all possible mensuration cutoff value from the T2DM individuality ability.Figure 15 is illustrated in eight kinds ROC curve in the label that provides in the table 1.Area under a curve scope from 0.84 to 0.99 proves and will carry out good differentiation between health volunteer and the experimenter.Saccharification and oxidation are too drastic owing to the protein variants that utilizes in producing curve.
For the purpose that the soft independent modeling (SIMCSA) that generates the branch analoglike is classified is carried out principal component analysis (PCA) (the PCA) (software that utilization is purchased: TheUnscrambler; CamoSoftware, Inc., Woodbridge, NJ).Figure 16 illustrates the result that the PC1 from the saccharification data is drawn with respect to the PC1 from the oxidation data.The individuality of cluster health in low saccharification, suboxides quadrant, just, the quadrant of " health " saccharification and oxidation, it is used as the reference point of T2DM, and is in case by the purpose of the treatment of the T2DM after making a definite diagnosis.Most individualities among the T2DM experimenter fall in the quadrant of high saccharification, high oxidation.About 20% (X ' s) of T2DM individuality presents good relatively saccharification control, but oxidative stress raises.
Reference:
1.American?Diabetes?Asssociation(2008)Economic?costs?of?diabetes?in?theU.S.in?2007,Diabetes?care?31,1-20.
2.National?Diabetes?Fact?Sheet.
http://www.cdc.gov/diabetes/pubs/pdf/ndfs2005.pdf
3.Feuerstein,B.L.,and?Weinstock,R.S.(1997)Diet?and?exercise?in?type2diabetes?mellitus,Nutrition?(Burbank,Los?Angeles?County,Calif?13,95-99.
4.Henry,R.R.,and?Gumbiner,B.(1991)Benefits?and?limitations?of?very-low-calorie?diet?therapy?in?obese?NIDDM,Diabetes?care?14,802-823.
5.Horton,E.S.(1988)Role?and?managementof?exercise?in?diabetesmellitus,Diabetes?care?11,201-211.
6.Ruderman,N.,Apelian,A.Z.,and?Schneider,S.H.(1990)Exerclse?intherapy?and?prevention?of?type?II?diabetes.Implications?for?blacks,Diabetes?care?13,1163-1168.
7.Scheen,A.J.(1998)Aggressive?welght?reduction?treatment?in?themanagement?of?type?2?diabetes,Diabetes?&metabolism?24,116-123.
8.Dawes,J.(2006)The?Role?of?Exercise?in?the?Prevention?and?Treatmentof?Gestational?Diabetes?Mellitus,Strength?and?Conditioning?Joumal?28,66-68.
9.Calvert,M.J.,McManus,R.J.,and?Freemantle,N.(2007)Themanagement?of?people?with?type?2diabetes?with?hypoglycaemic?agentsin?primary?care:retrospective?cohort?study,Family?practice?24,224-229.
10.Hermann,L.S.,Lindberg,G.,Lindblad,U.,and?Meander,A.(2002)Efflcacy,effectiveness?and?safety?of?sulphonylurea-metformincombination?therapy?in?patients?with?type?2?diabetes,Diabetes,obesity?&metabolism?4,296-304.
11.Davis,S.N.(2006)Insulin,Oral?Hypoglycemic?Agents,and?thePharmacology?of?the?Endocrlne?Pancreas,in?Goodman?and?Gllman′sThe?Pharmacological?Basis?of?Therapeutics?(Brunton,L.L.,Ed.)11thed.,McGraw-Hill,New?York.
12.Garber,A.J.,Ligthelm,R.,Christiansen,J.S.,and?Liebl,A.(2007)Premixed?insulin?treatment?for?type?2diabetes:analogue?or?human?,Diabetes,obesity?&metabolism?9,630-639.
13.Ahren,B.,Simonsson,E.,Larsson,H.,Landin-Olsson,M.,Torgeirsson,H.,Jansson,P.A.,Sandqvist,M.,Bavenholm,P.,Efendic,S.,Eriksson,J.W.,Dickinson,S.,and?Holmes,D.(2002)Inhibition?of?dipeptidylpeptidase?IV?improves?metabolic?control?over?a?4-week?study?period?intype?2diabetes,Diabetes?care25,869-875.
14.Ashiya,M.,and?Smith,R.E.T.(2007)Non-insuiin?therapies?for?type?2diabetes,Nature?Reviews:Drug?Discovery?6,777-778.
15.Peters,A.L.,and?Schriger,D.L.(1998)The?new?diagnostic?criteria?fordiabetes:the?impact?on?management?of?diabetes?and?macrovascular?riskfactors,The?American?journal?of?medicine?105,15S-19S.
16.Nelson,R.W.,Krone,J.R.,Bieber,A.L.,and?Willlams,P.(1995)Massspectrometric?immunoassay,Anal?Chem?67,1153-1158.
17.Krone,J.R.,Nelson,R.W.,and?Williams,P.W.(1996)Massspectrometric?immunoassay,Proceedings?of?SPIE?2680,415.
18.Intrlnsic?Bioprobes,inc. http://www.intrinsicbio.com?Tempe,AZ
19.Kiernan,U.A.,Tubbs,K.A.,Gruber,K.,Nedelkov,D.,Niederkofler,E.E.,Williams,P.,and?Nelson,R.W.(2002)High-throughput?proteincharacterization?using?mass?spectrometric?immunoassay,Anal?Biochem301,49-56.
20.Kiernan,U.A.,Addobbati,R.,Nedelkov,D.,and?Nelson,R.W.(2006)Quantitative?multiplexed?C-reactive?protein?mass?spectrometricimmunoassay,J?Proteome?Res?5,1682-1687.
21.Kiernan,U.A.,Nedelkov,D.,and?Nelson,R.W.(2006)Muitiplexed?massspectrometric?immunoassay?in?biomarker?research:a?novel?approach?tothe?determination?of?a?myocardial?infarct,J?Proteorne?Res?5,2928-2934.
22.Kiernan,U.A.,Nedelkov,D.,Niederkofler,E.E.,Tubbs,K.A.,andNelson,R.W.(2006)High-throughput?affinity?mass?spectrometry,Methods?Mol?Biol328,141-150.
23.Kiernan,U.A.,Nedelkov,D.,Tubbs,K.A.,Niederkofler,E.E.,andNelson,R.W.(2004)Proteomic?characterization?of?novel?serum?amyloidP?component?variants?from?human?plasma?and?urine,Proteomics?4,1825-1829.
24.Kiernan,U.A.,Nedelkov,D.,Tubbs,K.A.,Niederkofler,E.E.,andNelson,R.W.(2004)Selected?expression?proflling?of?full-length?proteinsand?their?variants?in?human?plasma,Clin?Proteomics?1,7-16.
25.Kiernan,U.A.,Tubbs,K.A.,Nedelkov,D.,Niederkofler,E.E.,McConnell,E.,and?Nelson,R.W.(2003)Comparative?urine?proteinphenotyping?using?mass?spectrometric?immunoassay,J?Proteome?Res?2,191-197.
26.Kiernan,U.A.,Tubbs,K.A.,Nedelkov,D.,Nlederkofler,E.E.,andNelson,R.W.(2002)Comparative?phenotypic?analyses?of?humanplasma?and?urinary?retinol?binding?protein?using?mass?spectrometricimmunoassay,Biochem?Biophys?Res?Commun?297,401-405.
27.Kiernan,U.A.,Tubbs,K.A.,Nedelkov,D.,Niederkofler,E.E.,andNelson,R.W.(2003)Detection?of?novel?truncated?forms?of?human?serumamyloid?A?protein?in?human?plasma,FEBS?Lett?537,166-170.
28.Nedelkov,D.(2006)Mass?spectrometry-based?immunoassays?for?thenext?phase?of?clinical?applications,Expert?review?of?proteomics?3,631-640.
29.Nedelkov,D.,Kiernan,U.A.,Niederkofler,E.E.,Tubbs,K.A.,andNelson,R.W.(2005)Investigating?diversity?in?human?plasma?proteins,Proc?Natl?Acad?Sci?U?S?A?102,10852-10857.
30.Nedelkov,D.,Kiernan,U.A.,Niederkofler,E.E.,Tubbs,K.A.,andNelson,R.W.(2006)Population?proteomics:the?concept,attributes,andpotential?for?cancer?biomarker?research,Mol?Cell?Proteomics?5,1811-1818.
31.Nedelkov,D.,and?Nelson,R.W.(2006)Surface?plasmon?resonancemass?spectrometry?for?protein?anaiysis,Methods?Mol?Biol?328,131-139.
32.Nedelkov,D.,Phillips,D.A.,Tubbs,K.A.,and?Nelson,R.W.(2007)Investigation?of?human?protein?variants?and?their?frequency?in?the?generalpopulation,Mol?Cell?Proteomics?6,1183-1187.
33.Nedelkov,D.,Tubbs,K.A.,Niederkofler,E.E.,Kiernan,U.A.,andNelson,R.W.(2004)High-throughput?comprehensive?analysis?of?humanplasma?proteins:a?step?toward?population?proteomics,Anal?Chem?76,1733-1737.
34.Nelson,R.W.,Nedelkov,D.,Tubbs,K.A.,and?Kiernan,U.A.(2004)Quantitative?mass?spectrometric?immunoassay?of?insulin?like?growthfactor?1,J?Proteome?Res?3,851-855.
35.Niederkofler,E.E.,Tubbs,K.A.,Gruber,K.,Nedelkov,D.,Kiernan,U.A.,Willlams,P.,and?Neison,R.W.(2001)Determination?of?beta-2microglobulin?levels?in?plasma?using?a?high-throughput?massspectrometric?immunoassay?system,Anal?Chem?73,3294-3299.
36.Niederkofler,E.E.,Tubbs,K.A.,Kiernan,U.A.,Nedelkov,D.,andNelson,R.W.(2003)Novel?mass?spectrometric?immunoassays?for?therapid?structural?characterization?of?plasma?apolipoprotelns,J?Lipid?Res44,630-639.
37.Tubbs,K.A.,Kiernan,U.A.,Niederkofler,E.E.,Nedelkov,D.,Bieber,A.L.,and?Neison,R.W.(2005)High-throughput?MS-based?proteinphenotyping:application?to?haptoglobin,Proteomics?5,5002-5007.
38.Tubbs,K.A.,Kiernan,U.A.,Niederkofler,E.E.,Nedelkov,D.,Bieber,A.L.,and?Nelson,R.W.(2006)Development?of?recombinant-based?massspectrometric?immunoassay?with?appication?to?resistln?expressionproflling,Anal?Chem?78,3271-3276.
39.Tubbs,K.A.,Nedelkov,D.,and?Nelson,R.W.(2001)Detection?andquantification?of?beta-2-miorogiobulin?using?mass?spectrometricimmunoassay,Anal?Biochem?289,26-35.
40.Nelson,R.W.(1999)Sample?presentation?apparatus?for?massspectrometry,(USPTO,Ed.),USA?Patent?No.6,004,770.
41.Nelson,R.W.(2000)Mass?spectrometer?having?a?derivatized?samplepresentation?apparatus,(USPTO,Ed.),USA?Patent?No.6,093,541.
42.Nelson,R.W.(2001)Sample?presentation?apparatus?for?massspectrometry,(USPTO,Ed.),USA?Patent?No.6,316,266.
43.Nelson,R.W.(2002)Sample?presentation?apparatus?for?massspectrometry,(USPTO,Ed.),USA?Patent?No.6,498,039.
44.Nelson,R.W.,and?Nedelkov,D.(2003)Bioacttve?chip?massspectrometry,(USPTO,Ed.),USA?Patent?No.6,569,383.
45.Nelson,R.W.,and?Nedelkov,D.(2005)Bioactive?chip?massspectrometry,(USPTO,Ed.),USA?Patent?No.6,887,713.
46.Nelson,R.W.,Willlams,P.,and?Krone,J.R.(2005)Mass?spectrometricimmunoassay,(USPTO,Ed.),USA?Patent?No.6,974,704.
47.Nelson,R.W.,Willlams,P.,and?Krone,J.R.(2007)Mass?spectrometricimmunoassay,(USPTO,Ed.),USA?Patent?No.7,303,888.
48.Tubbs,K.A.,Gruber,K.F.,and?Nelson,R.W.(2004)Integrated?highthroughput?system?for?the?mass?spectrometry?of?biomolecules,(USPTO,Ed.),USA?Patent?No.6,783,672.
49.Tubbs,K.A.,Gruber,K.F.,and?Nelson,R.W.(2006)Integrated?highthroughput?system?for?the?analysls?of?biomolecules,(USPTO,Ed.),USAPatent?No.7,087,165.
50.Tubbs,K.A.,Gruber,K.F.,and?Nelson,R.W.(2007)Integrated?highthroughput?system?for?the?mass?spectrometry?of?biomolecules,(USPTO,Ed.),USA?Patent?No.7,311,826.
51.Mclntosh,M.(2007)The?need?to?characterize?and?report?the?normalheterogeneity?of?proteins?in?clinical?biological?samples,J?Proteome?Res6,2913.
52.Breiman,L.(2001)Random?Forests,Machine?Learning?45,5-32.
53.Speeckaert,M.,Huang,G.,Delanghe,J.R.,and?Taes,Y.E.(2006)Biologlcal?and?clinical?aspects?of?the?vitamin?D?binding?protein?(Gc-globulin)and?its?polymorphism,Cllnica?chimica?acta;international?journalof?clinical?chemistry?372,33-42.
54.Cooke,N.E.,and?Haddad,J.G.(1989)Vitamin?D?binding?protein?(Gc-globulin),Endocrine?reviews?10,294-307.
55.Daiger,S.P.,Schanfield,M.S.,and?Cavaalli-Sforza,L.L.(1975)Group-specific?component?(Gc)proteins?bind?vitamin?D?and?25-hydroxyvitaminD,Proc?Natl?Acad?Sci?U?S?A?72,2076-2080.
56.Ena,J.M.,Esteban,C.,Perez,M.D.,Uriel,J.,and?Calvo,M.(1989)Fatty?acids?bound?to?vitamin?D-binding?protein?(DBP)from?human?andbovine?sera,Biochemistry?intemational?19,1-7.
57.Williams,M.H.,Van?Alstyne,E.L.,and?Galbraith,R.M.(1988)Evidenceof?a?novel?association?of?unsaturated?fatty?acids?with?Gc?(vitamin?D-binding?protein),Biochem?Biophys?Res?Commun?153,1019-1024.
58.Homma,S.,Yamamoto,M.,and?Yamamoto,N.(1993)Vitamin?D-bindingprotein?(group-speciflc?component)is?the?sole?serum?protein?required?formacrophage?activation?after?treatment?of?peritoneal?cells?withlysophosphatidylcholine,Immunology?and?cell?biology?71(Pt?4),249-257.
59.Yamamoto,N.,and?Kumashiro,R.(1993)Conversion?of?vitamin?D3binding?protein?(group-specific?component)to?a?macrophage?activatingfactor?by?the?stepwise?action?of?beta-galactosldase?of?B?cells?andslalldase?of?T?cells,J?Immunol?151,2794-2802.
60.Hirai,M.,Suzuki,S.,Hinokio,Y.,Chiba,M.,Kasuga,S.,Hirai,A.,andToyota,T.(1998)Group?specific?component?protein?genotype?isassociated?with?NIDDM?in?Japan,Diabetologia?41,742-743.
61.Klupa,T.,Malecki,M.,Hanna,L.,Sieradzka,J.,Frey,J.,Warram,J.H.,Sieradzki,J.,and?Krolewski,A.S.(1999)Amino?acid?varlants?of?thevitamin?D-binding?protein?and?risk?of?dlabetes?in?white?Americans?ofEuropean?origin,European?journal?of?endocrinology/EuropeanFederation?of?Endocrine?Societies?141,490-493.
62.Malecki,M.T.,Klupa,T.,Wanic,K.,Cyganek,K.,Frey,J.,and?Sieradzkl,J.(2002)Vitamin?D?binding?protein?gene?and?genetic?susceptibility?totype?2?dlabetes?mellitus?in?a?Polish?population,Diabetes?research?andclinical?practice?57,99-104.
63.Ye,W.Z.,Dubois-Laforgue,D.,Bellanne-Chantelot,C.,Timsit,J.,andVelho,G.(2001)Variations?in?the?vitamin?D-binding?protein?(Gc?locus)and?rlsk?of?type?2diabetes?mellitus?in?French?Caucasians,Metabolism:clinical?and?experirmental?50,366-369.
64.Petricoin,E.F.,Ardekani,A.M.,Hitt,B.A.,Levine,P.J.,Fusaro,V.A.,Steinberg,S.M.,Mills,G.B.,Simone,C.,Fishman,D.A.,Kohn,E.C.,and?Liotta,L.A.(2002)Use?of?proteomic?pa?tterns?in?serum?to?Identifyovarian?cancer,Lancet?359,572-577.
65.Baggerly,K.A.,Morris,J.S.,Edmonson,S.R.,and?Coombes,K.R.(2005)Signal?in?noise:evaluating?reported?reproducibility?of?serumproteomic?tests?for?ovarian?cancer,Journal?of?the?National?CencerInstitute?97,307-309.
66.Characteristics?of?beta-2-microglobulin.
http://web.lfp.cuni.cz/iournals/imj/1998/1/415-en.html
67.Filler,G.,Bokenkamp,A.,Hofmann,W.,Le?Bricon,T.,Martinez-Bru,C.,and?Grubb,A.(2005)Cystatin?C?as?a?marker?of?GFR-history,indications,and?future?research,Clin?Biochem?38,1-8.
68.Safadi,F.F.,Thornton,P.,Magiera,H.,Hollis,B.W.,Gentile,M.,Haddad,J.G.,Liebhaber,S.A.,and?Cooke,N.E.(1999)Osteopathyand?resistance?to?vitamin?D?toxicity?in?mice?null?for?vitamin?D?bindingprotein,J?Clin?Invest?103,239-251.
69.Rifai,N.,Gillette,M.A.,and?Carr,S.A.(2006)Protein?biomarkerdiscovery?and?validation:the?long?and?uncertain?path?to?clinical?utility,Nat?Biotechno/24,971-983.
70.Hermanson,G.T.,Krishna?Mallia,A.,and?Smith,P.K.(1992)Immobilized?Affinity?Ligand?Technigues,Academic?Press,San?Diego,CA.
71.Anderson,L.(2005)Candidate-based?proteomics?in?the?search?forbiomarkers?of?cardiovascular?disease,J?Physio/563,23-60.
72.Anderson,N.L.,Polanski,M.,Pieper,R.,Gatlin,T.,Tirumalai,R.S.,Conrads,T.P.,Veenstra,T.D.,Adkins,J.N.,Pounds,J.G.,Fagan,R.,and?Lobley,A.(2004)The?human?plasma?proteome:a?nonredundant?listdeveloped?by?combination?of?four?separate?sources,Mol?Cell?Proteomics3,311-326.
73.Jaleel,A.,Halvatsiotis,P.,Willimson,B.,Juhasz,P.,Martin,S.,andNair,K.S.(2005)Identification?of?Amadori-modlfied?plasma?proteins?intype?2diabetes?and?the?effect?of?short-term?intensive?insulin?treatment,Diabetes?care?28,645-652.
74.Nelson,R.W.(1997)The?use?of?bioreactive?probes?in?proteincharacterization,Mass?Spectrometry?Reviews?16,353-376.
75.Bieber,A.L.,Tubbs,K.A.,and?Nelson,R.W.(2004)Metal?LigandAffinity?Pipettes?and?Bioreactive?Alkaline?Phosphatase?Probes?Tools?forCharacterization?of?Phosphorylated?Proteins?and?Peptides *,Molecular?&Cellular?Proteomics?3,266-272.
76.Nelson,R.W.,Dogruel,D.,Krone,J.R.,and?Williams,P.(1995)Peptidecharacterization?using?bioreactive?mass?spectrometer?probe?tips,RapidCommun?Mass?Spectrom?9,1380-1385.
77.Tubbs,K.A.,Nelson,R.W.,Krone,J.R.,and?Bleber,A.L.(2005)MASSSPECTRAL?STUDIES?OF?SNAKE?VENOMS?AND?SOME?OF?THEIRTOXINS,Toxin?Reviews?19,1-22.
78.Nelson,R.W.,Lewis,J.K.,Dogruel,D.,Krone,J.R.,and?Williams,P.W.(1996)Rapid?protein?characterization?using?bioreactive?massspectrometer?probe?tips,Proceedings?of?SPIE?2680,390.
79.Dogruel,D.,Williams,P.,and?Nelson,R.W.(1995)Rapid?TrypticMapping?Using?Enzymically?Active?Mass?Spectrometer?Probe?TipsAnalytical?Chemistry?67,4343-4348.
80.Pribyl,J.,and?Skladal,P.(2006)Development?of?a?combined?setup?forsimultaneous?detection?of?total?and?glycated?haemoglobin?content?inblood?samples,Biosens?Bioelectron?21,1952-1959.
81.Brancia,F.L.,Bereszczak,J.Z.,Lapoila,A.,Fedele,D.,Baccarin,L.,Seraglia,R.,and?Traldi,P.(2006)Comprehensive?analysis?of?glycatedhuman?serum?albumin?tryptic?peptides?by?off-lina?liquid?chromatographyfollowed?by?MALDI?analysis?on?a?time-of-flight/curved?field?reflectrontandem?mass?spectrometer,J?Mass?Spectrom?41,1179-1185.
82.Elwood,M.(2002)Proteomic?pattemns?in?serum?and?identification?ofovarian?cancer,Lancet?360,170;author?reply?170-171.
83.Nakhoul,F.M.,Miller-Lotan,R.,Awaad,H.,Asleh,R.,and?Levy,A.P.(2007)Hypothesis--haptoglobin?genotype?and?diabetic?nephropathy,Nature?clinical?practice?3,339-344.
84.Quaye,I.K.,Ababio,G.,and?Amoah,A.G.(2006)Haptoglobin?2-2phenotype?is?a?risk?factor?for?type?2?diabetes?in?Ghana,Joumnal?ofatherosclerosis?and?thrombosis?13,90-94.
85.Stephens,J.W.,Sozen,M.M.,Whittall,R.A.,Casiake,M.J.,Bedford,D.,Acharya,J.,Hurel,S.J.,and?Humphries,S.E.(2005)Three?novelmutations?in?the?apolipoprotein?E?gene?in?a?sample?of?individuals?withtype?2diabetes?mellitus,Clin?Chem?51,119-124.
86.Merchant,M.,and?Weinberger,S.R.(2000)Recent?advancements?insurface-enhanced?laser?desorption/ionization-time?of?flight-massspectrometry,Electrophoresis?21,1164-1177.
87.Anderson,N.L.,Anderson,N.G.,Haines,L.R.,Hardie,D.B.,Olafson,R.W.,and?Pearson,T.W.(2004)Mass?spectrometrlc?quantitation?ofpeptides?and?proteins?using?stable?isotope?standards?and?capture?byanti-peptide?antibodies(SISCAPA),J.Proteome?Res?3,235-244.
88.Sykes,K.F.,and?Johnston,S.A.(1999)Linear?expression?elements:arapid,in?vivo,method?to?screen?for?gene?functions,Nat?Biotechnol?17,355-359.
89.Nelson,R.W.,Jarvik,J.W.,Taillon,B.E.,and?Tubbs,K.A.(1999)BIA/MS?of?epitope-tagged?peptides?directly?from?E.coli?lysate:multiplexdetection?and?protein?identification?at?low-femtomole?to?subfemtomolelevels,Anal.Chem?71,2858-2865.
90.Schmidt,A.M.,Hori,O.,Brett,J.,Yan,S.D.,Wautler,J.L.,and?Stern,D.(1994)Cellular?receptors?for?advanced?glycation?end?products.Implications?for?induction?of?oxidant?stress?and?cellular?dysfunction?in?thepathogenesis?of?vascular?lesions,Arteriosclerosis,Thrombosis,andVascular?Biology?14,1521-1528.
91.Brownlee,M.(1995)Advanced?protein?glycosylation?in?diabetes?andaging,Annu?Rev?Med?46,34.
92.Raj,D.S.,Choudhury,D.,Welbourne,T.C.,and?Levi,M.(2000)Advanced?glycation?end?products:a?Nephroiogist′s?perspective,Am?JKidney?Dis?35,365-380.

Claims (14)

1. be used for detection and monitoring of diseases or disorderly method in the experimenter, comprise the genetic mutation (GM) that detects and be determined in the subject liquid eggs white matter, translate the back and modify the biomarker that (PTM) or metabolism change (MA).
2. method according to claim 1, wherein disease or disorder are diabetes.
3. method according to claim 1, wherein body fluid protein is blood plasma or urine protein.
4. method according to claim 1, wherein the data that obtain from a plurality of labels utilize sorting algorithm further to assess so that set up health and diabetic disease states.
5. method according to claim 1, wherein biomarker is associated with volume lifetime so that foundation and the diabetes longitudinal recording relevant with the prediabetes state.
6. method according to claim 1, wherein biomarker is associated with volume lifetime so that set up the longitudinal recording relevant with treatment with the processing of diabetes.
7. method according to claim 1, wherein disease or the disorderly group that constitutes by following that is selected from: diabetes, angiocardiopathy, crown and peripheral arterial disease, chronic obstructive pulmonary disease, apoplexy, cancer, senile dementia, neuropathy, retinopathy and deficiency disease; Above-mentioned is independent a kind of disease or the conduct common disease related with diabetes.
8. method according to claim 1, wherein biomarker is the saccharification biomarker that is selected from by the following group that constitutes: Gc-globulin (GcG), B2M (b2m), cysteine proteinase inhibitor C (cysC), albumin (Albumin) and Hem A﹠amp; B.
9. method according to claim 1, wherein biomarker is the oxidation biomarker that is selected from by the following group that constitutes: albumin (Albumin), TTR, Apo A1 and ApoC1.
10. method according to claim 1, wherein biomarker is the enzyme biomarker that is selected from the group that is made of C-peptide (C-pep) and insulin.
11. be used for detection and monitoring of diseases or disorderly method in the experimenter, comprise by utilizing multiple mensuration to determine and disease or disorderly relevant GM, PTM, and/or the combination of MA biomarker.
12. be used for detection and monitoring of diseases or disorderly method in the experimenter, comprise by utilizing single mensuration to determine and disease or disorderly relevant GM, PTM, and/or the combination of MA biomarker.
13. method according to claim 11, GM wherein, PTM and MA biomarker all are present on the same gene prod and the analysis based on protein that can be single detects.
14. method according to claim 12, GM wherein, PTM and MA biomarker all are present on the same gene prod and the analysis based on protein that can be single detects.
CN2009801179321A 2008-03-17 2009-03-17 Biomarkers and assays for diabetes Pending CN102171572A (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US6967408P 2008-03-17 2008-03-17
US61/069,674 2008-03-17
PCT/US2009/037369 WO2009117395A2 (en) 2008-03-17 2009-03-17 Biomarkers and assays for diabetes

Publications (1)

Publication Number Publication Date
CN102171572A true CN102171572A (en) 2011-08-31

Family

ID=41091489

Family Applications (1)

Application Number Title Priority Date Filing Date
CN2009801179321A Pending CN102171572A (en) 2008-03-17 2009-03-17 Biomarkers and assays for diabetes

Country Status (7)

Country Link
US (1) US20110250618A1 (en)
EP (1) EP2271942A2 (en)
JP (1) JP2011515680A (en)
CN (1) CN102171572A (en)
AU (1) AU2009225713A1 (en)
CA (1) CA2715023A1 (en)
WO (1) WO2009117395A2 (en)

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9817001B2 (en) 2008-05-27 2017-11-14 Boston Heart Diagnostics Corporation Methods for determining LDL cholesterol treatment
US8470541B1 (en) 2008-09-27 2013-06-25 Boston Heart Diagnostics Corporation Methods for separation and immuno-detection of biomolecules, and apparatus related thereto
CN101937000A (en) * 2010-08-05 2011-01-05 北京倍爱康生物技术有限公司 Magnetic particle separation chemiluminescence immunoassay method of human cystatin C
CN102539779A (en) * 2010-12-27 2012-07-04 中国科学院上海生命科学研究院 Application of Vitamin D binding protein serving as marker of diabetes
EP2766728B1 (en) 2011-10-13 2017-09-06 Boston Heart Diagnostics Compositions and methods for treating and preventing coronary heart disease
KR102138106B1 (en) * 2012-01-31 2020-07-28 더유니버시티오브톨레도 Methods and devices for detection and measurement of analytes
CN103376326A (en) * 2012-04-25 2013-10-30 中国科学院上海生命科学研究院 Application of vitamin D binding protein as obesity-diabetes marker
CN103376325A (en) * 2012-04-25 2013-10-30 中国科学院上海生命科学研究院 Application of angiotensinogen protein precursor as obesity-diabetes marker
US20140120559A1 (en) * 2012-10-26 2014-05-01 Boston Heart Diagnostics Corporation Diabetes panel
JP6196034B2 (en) 2012-12-20 2017-09-13 ライオン株式会社 Marker peptide for determining hyperglycemia risk and use thereof
CN114324893A (en) * 2012-12-26 2022-04-12 奎斯特诊断投资公司 C-peptide detection by mass spectrometry
EP2999958B1 (en) 2013-05-21 2019-09-18 Dh Technologies Dev Pte Ltd Species detection using mass spectrometry
US9828624B2 (en) 2013-07-24 2017-11-28 Boston Heart Diagnostics Corporation Driving patient compliance with therapy
WO2015112429A1 (en) 2014-01-23 2015-07-30 Newomics Inc Methods and systems for diagnosing diseases
GB201415367D0 (en) 2014-08-29 2014-10-15 Iles Raymond K And Docherty Suzanne M E And Abban Thomas And Naase Mahmoud And Iles Jason K Methods for detecting abnormalities in haemoglobin
GB201415369D0 (en) * 2014-08-29 2014-10-15 Iles Raymond K Rapid screening and evaluation of diabetes and prediabetes by glycated haemoglobin mass spectrometry
WO2016081471A1 (en) 2014-11-17 2016-05-26 Boston Heart Diagnostic Corporation Cardiovascular disease risk assessment
WO2016118489A1 (en) * 2015-01-19 2016-07-28 Siscapa Assay Technologies, Inc. Combined analysis of small molecules and proteins by mass spectrometry
WO2016183521A1 (en) * 2015-05-13 2016-11-17 Newomics Inc. Methods and systems for biomonitoring
EP3667301B1 (en) 2018-12-10 2021-12-01 Roche Diabetes Care GmbH Method and system for determining concentration of an analyte in a sample of a bodily fluid, and method and system for generating a software-implemented module

Also Published As

Publication number Publication date
US20110250618A1 (en) 2011-10-13
EP2271942A2 (en) 2011-01-12
WO2009117395A2 (en) 2009-09-24
CA2715023A1 (en) 2009-09-24
JP2011515680A (en) 2011-05-19
AU2009225713A1 (en) 2009-09-24

Similar Documents

Publication Publication Date Title
CN102171572A (en) Biomarkers and assays for diabetes
Spiller et al. Plasma levels of free fatty acids correlate with type 2 diabetes mellitus
JP2017062264A (en) Protein biomarkers and lipid metabolite biomarkers providing consistent improvement to prevention of type 2 diabetes
US8476008B2 (en) Methods for detecting pre-diabetes and diabetes
Cañadas-Garre et al. Proteomic and metabolomic approaches in the search for biomarkers in chronic kidney disease
Bhat et al. Abundance matters: role of albumin in diabetes, a proteomics perspective
EP2353011B1 (en) Biomarker for the prediction of first adverse events
US20110319499A1 (en) Methods for the Detection of Advanced Glycation Endproducts and Markers for Disease
Zhi et al. Proteomic technologies for the discovery of type 1 diabetes biomarkers
WO2006116351A2 (en) Method for the early detection of renal disease using proteomics
Carter et al. Validation of a metabolite panel for early diagnosis of type 2 diabetes
EP2927692B1 (en) Multiple biomarker approach for prediction of mortality in dialysis patients
Bennett et al. Characteristics of an ideal biomarker of kidney diseases
Phillips HbA1c and monitoring glycaemia
Cho et al. Differential expression of proteins in kidney, eye, aorta, and serum of diabetic and non‐diabetic rats
Cheng et al. Factors associated with elevated plasma phenylalanine in patients with heart failure
Yadav et al. Interference of hemoglobin variants in HbA1c quantification
WO2005079410A2 (en) Biological profiles and methods of use
Jain et al. Hemoglobin Raleigh results in factitiously low hemoglobin A1c when evaluated via immunoassay analyzer
EP2451466B1 (en) Apolipoprotein ciii in pre- and type 2 diabetes
González et al. Urinary proteome of dogs with renal disease secondary to leishmaniosis
CN112684020B (en) Biomarker for evaluating zinc nutrition status of individual and application thereof
EP2533653B1 (en) Homoarginine as a biomarker for the risk of mortality
US20020072492A1 (en) Non-genetic based protein disease markers
Venos et al. Endocrine markers of diabetes and cardiovascular disease risk

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C53 Correction of patent of invention or patent application
CB03 Change of inventor or designer information

Inventor after: Nelson Randall W.

Inventor after: Borges Chad R.

Inventor after: Paul Ollan

Inventor before: Nelson Randall W.

Inventor before: Borges Chad R.

COR Change of bibliographic data

Free format text: CORRECT: INVENTOR; FROM: NELSON RANDALL W. BORGES CHAD R. TO: NELSON RANDALL W. BORGES CHAD R. ORANPAUL

C02 Deemed withdrawal of patent application after publication (patent law 2001)
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20110831